Dynamic Relationship between Gross Domestic Product and Domestic Investment in Rwanda
Why this work is in the frame
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Bibliographic record
Abstract
This study uses a VAR model to analyse the dynamic relationship between gross domestic product (GDP) and domestic investment (DI) in Rwanda for the period 1970 to 2011. Several selection lag criteria chose a maximum lag of one, and a bivariate VAR(1) model specification in levels was adopted. Unit root tests show that both GDP and DI series are nonstationary in levels but stationary in first differences, implying that both are integrated of order one I(1). Tests of cointegration established that GDP and DI are CI(1,1), suggesting there is a long-run equilibrium relationship between the two series. The error correction model indicates that DI adjusts to GDP with a lag whereby 0.2 percent of the discrepancy between long-term and short-term DI is corrected within the year. Granger causality tests show that there is unidirectional causality where GDP causes DI. The bivariate VAR (1) was unstable when estimated at levels, but was stable in first differences. Finally it was found out that GDP almost perfectly predicts DI in the estimated VAR (1) model. The forecasted value of DI in 2011 was 22.6% of GDP while the actual value was 22.7% of GDP. The small discrepancy may be attributed to the appropriate policy measures the Rwandan government and the private sector federation have thus far taken to facilitate investors in their businesses.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it